The Characteristics and Trend Prediction of Water and Sediment Evolution at the Toudaoguai Station on the Yellow River from 1960 to 2019

The Yellow River is a renowned sediment-laden river and analyzing its water–sediment evolution characteristics and trends is critical for rational water resource utilization and water security. Using annual runoff and sediment transport data from Toudaoguai Hydrological Station (1960–2019), Mann–Ken...

Full description

Saved in:
Bibliographic Details
Main Authors: Chao Li, Jing Guo, Xinlei Guo, Hui Fu
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Hydrology
Subjects:
Online Access:https://www.mdpi.com/2306-5338/12/7/174
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The Yellow River is a renowned sediment-laden river and analyzing its water–sediment evolution characteristics and trends is critical for rational water resource utilization and water security. Using annual runoff and sediment transport data from Toudaoguai Hydrological Station (1960–2019), Mann–Kendall tests, cumulative anomalies analysis, and wavelet analysis were used to investigate the decadal variations. A coupled ARIMA-BP model was developed to improve simulation accuracy over standalone ARIMA/BP models for trend prediction. The results showed significant decreasing trends in both runoff (Z = −3.22) and sediment transport (Z = −4.73) during 1960–2019, with change points in 1986 (runoff) and 1984 (sediment). The primary periodicities were 12 years for runoff and 31 years for sediment transport. The coupled model achieved good consistency (R<sup>2</sup> = 0.9142 for runoff, 0.8637 for sediment), outperforming individual models. Projections indicate continued declines in both variables from 2020 to 2029. Natural factors are the main cause affecting the changes in runoff, while human activities are the primary influencing factor for the changes in sediment load. This study introduces a novel approach for water–sediment analysis in the Yellow River Basin, providing technical support for sustainable water resource management.
ISSN:2306-5338